Process Discovery from Dependence-Complete Event Logs
Process Discovery from Dependence-Complete Event Logs
复制标题
DOI：
10.1109/tsc.2015.2426181
复制
发表时间：
2016-09
影响因子：
8.1
通讯作者：
Wei Song;H. Jacobsen;Chunyang Ye;Xiaoxing Ma
中科院分区：
文献类型：
--
作者：
Wei Song;H. Jacobsen;Chunyang Ye;Xiaoxing Ma
流程挖掘，特别是流程发现，已经被用来从事件日志中提取流程模型。进程发现面临的一个挑战是有效地识别并发性。国家的最先进的方法采用跟踪活动顺序进行过程发现，他们需要严格的事件日志的完整性概念。因此，当事件日志不能满足完整性标准时，它们可能无法提取适当的流程。为了解决这个问题，我们在本文中提出了一种新的技术，利用活动依赖的痕迹。基于没有依赖关系的活动可以并行执行的观察，即使日志未能满足完整性标准，我们的技术也能够发现具有并发性的流程。也就是说，我们的技术需要一个较弱的完整性概念。我们评估我们的技术，通过对真实世界和合成事件日志的实验，一致性检查结果表明，我们的技术的有效性和相对优势相比，国家的最先进的方法。
Process mining, especially process discovery, has been utilized to extract process models from event logs. One challenge faced by process discovery is to identify concurrency effectively. State-of-the-art approaches employ activity orders in traces to undertake process discovery and they require stringent completeness notions of event logs. Thus, they may fail to extract appropriate processes when event logs cannot meet the completeness criteria. To address this problem, we propose in this paper a novel technique which leverages activity dependences in traces. Based on the observation that activities with no dependencies can be executed in parallel, our technique is in a position to discover processes with concurrencies even if the logs fail to meet the completeness criteria. That is, our technique calls for a weaker notion of completeness. We evaluate our technique through experiments on both real-world and synthetic event logs, and the conformance checking results demonstrate the effectiveness of our technique and its relative advantages compared with state-of-the-art approaches.